Top AWS Jobs in Chennai

Develop and maintain scalable full-stack web applications across backend, frontend, databases, APIs, and cloud platforms. Responsibilities include designing applications, building services and responsive interfaces, optimizing SQL and NoSQL databases, integrating third-party services, troubleshooting production issues, writing secure maintainable code, and participating in testing, code reviews, and deployment. The role requires analytical problem-solving, understanding business requirements, effective communication, and adaptability across technology stacks.

Architect and build production-grade generative AI and agentic AI applications, including LLM workflows, multi-agent systems, RAG pipelines, APIs, and ML/GenAI infrastructure. Develop and optimize models, manage deployment and monitoring, apply responsible AI practices, and collaborate directly with customers. The role also involves mentoring engineers and shaping AI platform strategy.

Architects and builds scalable generative and agentic AI products from prototype through production. Designs LLM workflows, prompts, multi-agent systems, RAG pipelines, and APIs using LangChain and LangGraph. Owns ML and GenAI pipelines, including training, deployment, monitoring, and lifecycle management. Works directly with customers and cross-functional teams, promotes responsible AI, mentors engineers, and shapes AI platform strategy.

Provide architecture guidance and technical design for Case Management implementations using the Curam platform. Lead hands-on development and delivery across Curam services, Java/J2EE, databases, web technologies, workflows, rules, batch processing, and integrations. Collaborate with clients, systems integration partners, and project teams, while applying UI/UX, data architecture, cloud, DevOps, containerization, and Agile practices. Team leadership and extensive Curam and Java experience are required.

Design, develop, test, and deploy cloud-native microservices and APIs that run ML/AI algorithms on structured and unstructured telemetry data. Contribute code, automated tests, CI/CD pipelines, containerized deployments, and documentation while collaborating with product teams and geo-distributed stakeholders.

Manage and maintain HLR/HSS systems, provisioning platforms, SIM lifecycle operations, and core network components across multiple countries. Troubleshoot IMS call flows, VoLTE, VoWiFi, USSI, handover, and infrastructure incidents using Wireshark. Support HLR integrations, geographical expansion, capacity planning, process automation, and operational improvements while collaborating with network teams, architects, vendors, and country operations.

Own the production lifecycle for traditional ML and generative AI systems, including deployment pipelines, model registries, monitoring, retraining, governance, and incident response. Build reliable AWS-based infrastructure for LLM and agentic applications, establish observability and cost controls, and create operational standards, runbooks, and documentation. Partner with U.S.-based Data Science, Data Engineering, and Product teams while independently managing production workloads during India operating hours.

Design, build, test, and deploy production-grade agentic AI systems using Python, LangGraph, LangChain, AWS Bedrock, and orchestration tools. Integrate AI agents with APIs and business systems, implement memory and retrieval, establish observability and safeguards, and develop reusable SDKs and templates. Collaborate directly with clients to define requirements, run experiments, and rapidly deliver reliable AI solutions using modern software engineering, cloud deployment, and CI/CD practices.

Designs and maintains CI/CD pipelines, cloud infrastructure, infrastructure-as-code, and containerized environments. Improves scalability, reliability, security, monitoring, and automation; troubleshoots infrastructure and application issues; responds to incidents through on-call rotation; and collaborates with development and operations teams to support reliable software delivery.

Designs and maintains a centralized AI platform and agentic framework for secure enterprise deployment and access. Builds scalable AI agents, unified APIs, distributed systems, and microservices; integrates agents into customer and internal applications; optimizes cloud-native workloads; ensures security and regulatory compliance; and leads technical strategy, mentoring, performance analysis, and capacity planning.

Designs and maintains a centralized AI platform and agentic framework supporting secure deployment, management, and integration of AI agents. Responsibilities include building scalable agentic solutions, developing unified APIs, integrating agents into applications, optimizing cloud-native workloads, ensuring security and compliance, conducting capacity planning, mentoring engineers, and shaping the platform roadmap.

Provides post-sale technical and functional support for enterprise customers using Edifecs/Cotiviti Encounter Management products. Responsibilities include installation, configuration, upgrades, migrations, troubleshooting, hot-fix deployment, performance analysis, root-cause investigation, issue reproduction, automation scripting, custom utility development, and customer escalation management. The role partners with development, implementation, sustaining engineering, and sales engineering teams while mentoring other team members.

Lead backend engineering for a centralized AI platform, designing scalable REST APIs and Python services for agent lifecycle management, deployment, monitoring, authentication, authorization, and asynchronous workflows. Develop data layers and database schemas, contribute to distributed architecture and SDK design, and ensure reliability through testing, CI/CD, and security practices. Mentor engineers, guide technical decisions, and work with modern agentic AI frameworks.

Design, build, operate, and scale reliable cloud-native infrastructure for partner organizations. Manage Kubernetes clusters, CI/CD pipelines, observability platforms, infrastructure as code, and production incident response. Implement SRE practices including SLIs and SLOs, automate operational workflows using Go or Python, support 24/7 on-call coverage, and explore AI, AIOps, and GPU infrastructure. Contribute to technical documentation, presentations, and open-source projects.

Leads engineering for ERP data management, high-volume email processing, backend APIs, distributed systems, and service architecture. Owns reliability, scalability, security, observability, and iterative platform improvements for 24/7 systems. Acts as a liaison between engineering and business teams, mentors engineers, and collaborates across global teams in India, China, Singapore, and the United States. The role is fully remote from India and requires flexibility for global operations.

Design, develop, maintain, and deploy .NET-based web solutions across the full software lifecycle. Provide technical leadership, mentor junior engineers, collaborate with cross-functional and international teams, and drive continuous improvement of development practices.

Develop and maintain scalable Python backend applications, RESTful APIs, microservices, and asynchronous workflows. Design and optimize SQL and NoSQL databases, improve system performance and reliability, document APIs, implement RBAC and compliance controls, and resolve production incidents. Collaborate with frontend, DevOps, and product teams to deliver end-to-end features. Preferred experience includes Docker, Kubernetes, cloud platforms, Redis, ClickHouse, and basic frontend technologies.

Lead design, development, and deployment of Generative AI solutions using Azure OpenAI, Semantic Kernel, and langchain. Build CI/CD pipelines, ensure observability and system reliability, implement AI governance, collaborate with stakeholders, and apply Agile practices to deliver scalable AI applications.

Designs, develops, and maintains automated testing frameworks and processes. Executes automated test cases, analyzes results, troubleshoots scripts, and reports findings. Collaborates with cross-functional and distributed teams, contributes to technical solutions, and supports Agile SDLC and STLC practices. Requires strong Java, Selenium, Cucumber, Serenity, API automation, CI/CD, and debugging skills, with preferred experience in AWS, Docker, EKS, databases, Kafka, Spring, and REST services.

Own and operate AWS, Azure, and Databricks infrastructure supporting data engineering, data science, and MLOps teams. Responsibilities include cloud provisioning, networking, IAM, Unity Catalog administration, security controls, infrastructure as code, platform onboarding, automation, cost management, compliance evidence, troubleshooting, and operational documentation. The role establishes secure DEV, QA, and PROD environments and serves as the primary escalation point for Databricks and cloud platform issues.

Build and maintain batch and streaming data pipelines across AWS, Azure, and GCP using Databricks, Spark, PySpark, SQL, and Delta Lake. Implement medallion architecture, CDC, SCD, data quality, governance, security, metadata, and lineage controls. Configure storage, orchestration, CI/CD, monitoring, troubleshooting, and performance optimization. Collaborate with architects, data scientists, engineers, analysts, and product teams while documenting pipelines, transformations, testing, and operational procedures.

Build governed Databricks Lakehouse foundations and productionize machine learning and GenAI solutions, including forecasting, anomaly detection, NLP, RAG, and predictive analytics. Develop reliable batch and streaming workflows, CI/CD, monitoring, governance, security, lineage, and semantic models. Collaborate with product, data, platform, and domain teams to deliver measurable customer value while meeting reliability, compliance, cost, and operational objectives.

Supports sales teams and partners with technical cloud security sales activities, including solution integration, product demonstrations, evaluations, RFP responses, architecture discussions, and enablement training. Advises technical and executive audiences on Varonis cloud products, security analytics, and threat detection. Requires customer-facing communication skills, cloud platform expertise, and familiarity with SaaS administration and security technologies.

Lead architecture and delivery of a composable, API-first Core Commerce Platform powering checkout, payments, OMS, inventory availability, loyalty, and post-order experiences. Drive integration of packaged solutions (SFCC, Fluent Commerce), payments, social and agentic commerce, and AI-native capabilities. Own SLAs, reliability, security (PCI-DSS), roadmap, and engineering standards while building and leading high-performing, on-site platform teams.

Own application security across mobile apps, APIs, microservices, cloud infrastructure, AI products, and third-party integrations. Responsibilities include threat modeling, architecture reviews, penetration testing, secure coding, vulnerability management, incident response, SSDLC onboarding, CI/CD security tool integration, cloud hardening, developer training, and communicating risk. The role also assesses AI and LLM security risks and develops production guardrails and automation.